DOCSLIB.ORG

Challenges and Issues of Mining Crash Reports

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Challenges and Issues of Mining Crash Reports Challenges and Issues of Mining Crash Reports Le An, Foutse Khomh SWAT, Polytechnique Montreal,´ Quebec,´ Canada fle.an, [email protected] Abstract—Automatic crash reporting tools built in many soft- In the rest of this paper, we describe the structure of a ware systems allow software practitioners to understand the crash report before presenting some analytic techniques to origin of field crashes and help them prioritise field crashes mine implicit information from crash reports. For each of the or bugs, locate erroneous files, and/or predict bugs and crash occurrences in subsequent versions of the software systems. In techniques, we discuss its challenges and issues. After giving this paper, after illustrating the structure of crash reports in an overview of the related work, we conclude the paper with Mozilla, we discuss some techniques for mining information from suggestions for future studies. crash reports, and highlight the challenges and issues of these techniques. Our aim is to raise the awareness of the research II. STRUCTURE OF CRASH REPORTS community about issues that may bias research results obtained In this section, we take crash reports from Mozilla Socorro from crash reports and provide some guidelines to address certain server (Mozilla’s crash collecting database) [4] as an example challenges related to mining crash reports. Index Terms—Crash report, bug report, mining software to describe the typical crash collecting system. repositories. Mozilla delivers its applications with a built-in automatic crash reporting tool: Mozilla Crash Reporter, which sends a crash report to the Mozilla Socorro server, once end users I. INTRODUCTION encounter an unexpected halt of the application. Each crash Nowadays, crash reporting tools are embedded in many report records a stack trace of the falling thread and other software systems to collect information about crashes in the information about the user’s environment. A stack trace is an field (i.e., when a program stops functioning properly in a ordered set of frames where each frame indicates a method user environment). Crashes with the same crashing signature, signature and a link to the corresponding source code. Source the stack trace of the failing thread, will be grouped into code information is not always available in the frames, espe- a crash type. Usually, software quality managers prioritise cially when a frame belongs to a third party binary [1]. crash types by the number of crash occurrences, then file Crash Report – e1c1267874640-94324-32423 Each Crash Report is the top crash types into bug reports. Crash reports provide assigned a unique ID Crash Time - OCT 24, 2010 11:20:53 useful reference to analyse and resolve bugs. They could help Firefox Install Time – SEP 22, 2010 10:20:15 System Uptime – 1125 seconds software practitioners locate erroneous code, understand the Version- 3.6.13 User Environment impact of failures, and prioritise crash-related bug reports. OS – Windows NT 6.1 2600 Information CPU – x86 Leveraging crash reports, previous studies propose new User Comment – ideas to improve the current software maintenance techniques. Stack Trace – Frame Module Signature Source All crash Reports with top Khomh et al. [1] analysed crash reports of Mozilla Firefox 0 @0x654789 signature as 1 User32.dll UserCallWinProcCheckWow “UserCallWinCheckWow” are and proposed an entropy metric that reveals the distribution of 2 User32.dll DispatchMethod grouped together 3 User32.dll DispatchMessage the occurrences of crashes among end users. Wang et al. [2] Not all frames have Source 4 XUI.dll ProcessNextNativeEvent Src/win/nsAppShell.cpp:179 Information studied the crash reports of Firefox and stack traces of Eclipse. 5 XUI.dll nsShell::OnProcess Src/win/nsShell.cpp:77 6 Nspr4.dll mozilla::Pump Ipc/glue/MessagePump.cpp:134 They proposed five rules to automatically identify correlated 7 XUI.dll MessageLoop:Run Ipc/glue/MessageLoop.c:784 crash types. In a recent study, we also analysed crash reports from Mozilla products to identify bugs that affect a large Fig. 1: A sample crash report from Firefox population of users [3]. However, some inherent properties of crash reports may Figure 1 shows a sample crash report from Mozilla Firefox. challenge the research conclusions if researchers and software Among all information provided in a crash report, researchers practitioners do not take care of them when they mine infor- and software practitioners may be interested in the following mation from crash reports. For example, user information is attributes when they study crashes for software maintenance: not always available in crash reports, and the many-to-many • crash signature: top method signature of a crash. Crashes relationship between crashes and their related bugs increases with the same crash signature are grouped into one crash the difficulty of analysis. Furthermore, since there are not type in the Socorro server [1]. enough publicly opened crash collecting databases, researchers • Install age: the time in seconds from the installation until can hardly estimate the latent peril due to some of these the crash occurred. issues (e.g., lack of precise users’ information) or validate the • Crash date: the point of time when the crash was re- generalisability of their findings. ported. /15/$31.00 c 2015 IEEE 17 SWAN 2015, Montréal, Canada • OS name: name of the operating system on which the Algorithm 1: Map different crashed users to a crash type, crash occurred. and map different crash types to a bug • OS version: version of the operating system on which the Input: signature, user, buglist crash occurred. 1 if signature in dictcrash then • CPU type: family model of the CPU of a machine on 2 stackuser dictcrash[signature] which the crash occurred. 3 add user to stackuser 4 else • Bug list: list of bugs related to the crash. 5 stackuser new stack with user • Up time: the amount of seconds since the application 6 dictcrash[signature] stackuser startup. 7 foreach bug in buglist do Software researchers and practitioners can refer to the So- 8 if bug in bug dict then corro documentation [5] for the description of other attributes. 9 setsignature dictbug[bug] 10 add signature to setsignature 11 else III. ANALYSIS OF CRASH REPORTS AND CHALLENGES 12 setsignature new Set with signature In this section, we describe some analytic techniques of 13 dictbug[bug] setsignature crash reports for software maintenance and discuss their chal- lenges and issues. Algorithm 2: Map crashed user occurrences to their bugs A. User Identification Input: dictbug When we study crash reports, an important process is to 1 foreach bug in dictbug do identify unique users who encounter crashes in a software 2 setsignature dictbug[bug] 3 signature in set system. Mapping crashes to different users can help software foreach signature do 4 stackuser dictcrash[signature] practitioners understand the dispersion of these crashes in the 5 concatenate stackuser to occuruser user base and determine the priority of related crash types and bugs. However, user identity is not always available. For example, Mozilla crash reports do not contain personal information indicating unique users reporting the crashes due On the one hand, we can use the bug lists indicated in to privacy concerns. Khomh et al. [1] used a heuristic where crash reports to directly map crashes to bugs. However, some they took installed point of time (subtraction of crash date crashes are reported before the opening of their corresponding from install age) of the studied system to identify different bugs. If we apply the direct mapping only, we may omit the users (noted as install profiles). In our recent work [3], which information about these crashes. consisted in studying the crashing impact of bugs on the user On the other hand, we can also perform an indirect mapping population base, we used a vector of computer configuration from crashes to bugs via crash types. In other words, we (combination of CPU type, OS name, and OS version) to perform a two-step mapping as following: we map each bug represent different “users” (noted as machine profiles) in a to a set of crash types (i.e., a group of crashes with the system. same crash signature), then map each crash type to a set of However, these user identification heuristics may lead to crash reports. Concretely, we build two hash tables, dictbug inconsistent results. For example, when we apply the heuristic and dictcrash. In any item of dictbug, the key is a bug ID by install profile, two users who install an application at the and the value is a set of crash signatures. In any item of same point of time (by second) may encounter quite different dictcrash, the key is a crash signature and the value is a types of crashes. When we apply the heuristic by machine stack1 of crash reports. By associating the two hash tables, profile, users with the same computer configuration may also we can finally map a bug to a set of corresponding crash exhibit different crashing characteristics. In other words, users reports, even including those lacking bug information (i.e., that happened to install a software at the same time or in crashes reported before the creation of the bugs). Similarly, the same model of computer, especially for enterprise users to investigate the crash distribution in the user base, we can whose computers are uniformly configured or software is also link different users (represented by install profiles or simultaneously installed, may behave differently, and should machine profiles) to a bug by analysing the bug’s related crash not be clustered together in terms of crash analysis. reports. Algorithm 1 and 2 show the pseudocode to link a bug to the users suffering its related crashes.2 However, in B. Mapping between Crashes and Bugs a software system, a crash report may bring about several When we study the characteristics of bugs related to field bugs, a bug may be also related to more than one crashes.
Load more

Recommended publications
  • Crash Reporting: Mozilla’S Open Source Solution
    Crash Reporting: Mozilla’s Open Source Solution K Lars Lohn Ted Mielczarek Austin King Friday, July 24, 2009 Howdy, I’m Lars from Mozilla, I’m here today with my colleagues, Ted Mill-char-ek and Austin King to talk about Crash Reporting. What is it? Friday, July 24, 2009 Have you ever seen Firefox crash? Have you ever wondered what happens after you hit the “restart firefox” button? In the next 45 minutes, we’re going to take you down the rabbit hole and show you what we do. We want our processes to be open. When you experience a problem with any Mozilla product, we want _everyone_, not just the developers, to watch the flow of information about a problem for its initial occurrence, through data collection and triage, on to Bugzilla and to an eventual resolution. Crash reporting is the transmission of information to the developers about the state of an application during a catastrophic failure. Friday, July 24, 2009 Crash reporting is the transmission of information about the state of an application during a catastrophic failure to the developers. The goal is to give the developers information that they would not otherwise have had. Google Socorro Socorro UI Breakpad Server (reporter) minidump_stackwalk Friday, July 24, 2009 Our crash reporting system can be divided into three parts. Breakpad - a google project - this code lives mainly within the Firefox application Socorro (in two movements) the backend server and the user interface running at Mozilla. written in three languages <click> <click> <click> Ted, Austin and I are the three developers in charge of the three sections.
    [Show full text]
  • An Autopsy of a Web Browser's Leaked Crash Reports
    Crashing Privacy: An Autopsy of a Web Browser’s Leaked Crash Reports Kiavash Satvat Nitesh Saxena University of Alabama at Birmingham University of Alabama at Birmingham [email protected] [email protected] ABSTRACT private information that can be found in crash reports which may Harm to the privacy of users through data leakage is not an un- pose a threat to the users’ privacy. known issue, however, it has not been studied in the context of In this paper, to demonstrate possible risks that the current the crash reporting system. Automatic Crash Reporting Systems implementation of ACRS may pose to users’ privacy, we study a (ACRS) are used by applications to report information about the er- dataset of partially anonymized crash reports released by one of 1 rors happening during a software failure. Although crash reports the major browsers . The current state of the art browsers collect are valuable to diagnose errors, they may contain users’ sensitive relatively similar data including browsed URL during the crash and information. In this paper, we study such a privacy leakage vis-a- runtime information, as they can be required for the debugging. vis browsers’ crash reporting systems. As a case study, we mine To the best of our knowledge, this is the first case study which a dataset consisting of crash reports collected over the period of scrutinizes a database of 2.5 million partially anonymized crash re- six years. Our analysis shows the presence of more than 20,000 ports, containing visited URLs, system runtime information and sessions and token IDs, 600 passwords, 9,000 email addresses, an users’ descriptions.
    [Show full text]
  • Why Did This Reviewed Code Crash? an Empirical Study of Mozilla Firefox
    Why Did This Reviewed Code Crash? An Empirical Study of Mozilla Firefox Le An and Foutse Khomh Shane McIntosh Marco Castelluccio Polytechnique Montréal McGill University Mozilla Corporation and Università Federico II {le.an, foutse.khomh}@polymtl.ca [email protected] [email protected] Abstract—Code review, i.e., the practice of having other team mine the crash collection, version control, issue tracking, and members critique changes to a software system, is a pillar of code reviewing systems of the Mozilla Firefox project. More modern software quality assurance approaches. Although this specifically, we address the following two research questions: activity aims at improving software quality, some high-impact defects, such as crash-related defects, can elude the inspection of RQ1: What are the characteristics of reviewed code that is reviewers and escape to the field, affecting user satisfaction and implicated in a crash? increasing maintenance overhead. In this research, we investigate We find that crash-prone reviewed patches often contain the characteristics of crash-prone code, observing that such code complex code, and classes with many other classes de- tends to have high complexity and depend on many other classes. In the code review process, developers often spend a long time on pending on them. Crash-prone patches tend to take a and have long discussions about crash-prone code. We manually longer time and generate longer discussion threads than classify a sample of reviewed crash-prone patches according to non-crash-prone patches. This result suggests that review- their purposes and root causes. We observe that most crash- ers need to focus their effort on the patches with high prone patches aim to improve performance, refactor code, add complexity and on the classes with a complex relationship functionality, or fix previous crashes.
    [Show full text]
  • City Research Online
    City Research Online City, University of London Institutional Repository Citation: Stankovic, V. and Strigini, L. (2009). A survey on online monitoring approaches of computer-based systems. London, UK: Centre for Software Reliability, City University London. This is the unspecified version of the paper. This version of the publication may differ from the final published version. Permanent repository link: https://openaccess.city.ac.uk/id/eprint/531/ Link to published version: Copyright: City Research Online aims to make research outputs of City, University of London available to a wider audience. Copyright and Moral Rights remain with the author(s) and/or copyright holders. URLs from City Research Online may be freely distributed and linked to. Reuse: Copies of full items can be used for personal research or study, educational, or not-for-profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. City Research Online: http://openaccess.city.ac.uk/ [email protected] A survey on online monitoring approaches of computer-based systems Prepared by: Vladimir Stankovic, Lorenzo Strigini Date : June 2009 Version : 2.6 1/29 This report 1 surveys forms of online data collection that are in current use (as well as being the subject of research to adapt them to changing technology and demands), and can be used as inputs to assessment of dependability and resilience, although they are not primarily meant for this use. 1. Introduction Monitoring the components of a system can be used to make decisions about the management of the system and thus control its behaviour.
    [Show full text]
  • The Unreasonable Effectiveness of Traditional Information Retrieval in Crash Report Deduplication
    The Unreasonable Effectiveness of Traditional Information Retrieval in Crash Report Deduplication Joshua Charles Eddie Antonio Santos Abram Hindle Campbell Department of Computing Department of Computing Department of Computing Science Science Science University of Alberta University of Alberta University of Alberta Edmonton, Canada Edmonton, Canada Edmonton, Canada [email protected] [email protected] [email protected] ABSTRACT Organizations like Mozilla, Microsoft, and Apple are flooded Ada is a senior software engineer at Lovelace Inc., a large with thousands of automated crash reports per day. Al- software development company. Lovelace has just shipped though crash reports contain valuable information for de- the latest version of their software to hundreds of thousands bugging, there are often too many for developers to examine of users. A short while later, as Ada is transitioning her team individually. Therefore, in industry, crash reports are often to other projects, she gets a call from the quality-assurance automatically grouped together in buckets. Ubuntu’s repos- team (QA) saying that the software she just shipped has itory contains crashes from hundreds of software systems a crashing bug affecting two-thirds of all users. Worse yet, available with Ubuntu. A variety of crash report bucket- Ada and her team can’t replicate the crash. What would ing methods are evaluated using data collected by Ubuntu’s really be helpful is if every time that crash was encountered Apport automated crash reporting system. The trade-off be- by a user, Lovelace would automatically receive a crash re- tween precision and recall of numerous scalable crash dedu- port [1], with some context information about what machine plication techniques is explored.
    [Show full text]
  • Supporting Software Development Based on Crash Report Mining and Analysis
    CrashAwareDev: Supporting Software Development based on Crash Report Mining and Analysis Leandro Beserra*y, Roberta Coelhoy *Informatics Superintendence yDepartment of Informatics and Applied Mathematics Federal University of Rio Grande do Norte Natal, Brazil [email protected], [email protected] Abstract— Exception handling mechanisms are a com- of a program [2], allowing exceptions to be th- mon feature of mainstream programming languages to rown, captured, and handled at different points deal with exceptional conditions. If on the one hand in the system. However, the exception handling they allow the programmer to prepare the code to deal code designed to make a system more robust often with exceptional conditions, on the other hand they can become a source of bugs that threatens the application works the other way around and become a burden robustness – studies have shown that uncaught exceptions programmers has to cope with, leading to bugs are the main cause of application crashes. To keep track such as the uncaught exceptions. The uncaught of crashes and enable an easier fault localization, several exceptions are the main cause of crashes in Java applications, nowadays, use crash reporting tools. In software systems [3]. A crash is an abnormal this work, we propose a tool named CrashAwareDev, behavior of a system that leads to the interruption integrated with the Eclipse IDE, which mines the in- formation available in crash reporting tools to support of its execution. programmers in their day-to-day activities. The proposed After a crash occurs, systems typically store tool alerts developers about the classes related to recent information related to the crash on crash report crashes and warns about source code characteristics (bug systems.
    [Show full text]
  • Privacy-Aware Remote Error Analysis on Commodity Software
    Panalyst: Privacy-Aware Remote Error Analysis on Commodity Software Rui Wang†, XiaoFeng Wang† and Zhuowei Li‡ †Indiana University at Bloomington, ‡Center for Software Excellence, Microsoft wang63,xw7 @indiana.edu, [email protected] { } Abstract typically achieved by running an error reporting tool on a client system, which gathers data related to an applica- Remote error analysis aims at timely detection and rem- tion’s runtime exception (such as a crash) and transmits edy of software vulnerabilities through analyzing run- them to a server for diagnosis of the underlying software time errors that occur on the client. This objective can flaws. This paradigm has been widely adopted by soft- only be achieved by offering users effective protection ware manufacturers. For example, Microsoft relies on of their private information and minimizing the perfor- WER to collect data should a crash happen to an applica- mance impact of the analysis on their systems without tion. Similar tools developed by the third party are also undermining the amount of information the server can extensively used. An example is BugToaster [27], a free access for understanding errors. To this end, we propose crash analysis tool that queries a central database using in the paper a new technique for privacy-aware remote the attributes extracted from a crash to seek a potential analysis, called Panalyst. Panalyst includes a client com- fix. These tools, once complemented by automatic anal- ponent and a server component. Once a runtime excep- ysis mechanisms [44, 34] on the server side, will also tion happens to an application, Panalyst client sends the contribute to quick detection and remedy of critical se- server an initial error report that includes only public in- curity flaws that can be exploited to launch a large-scale formation regarding the error, such as the length of the cyber attack such as Worm epidemic [47, 30].
    [Show full text]
  • Statistical Debugging
    Statistical Debugging Ben Liblit, University of Wisconsin–Madison What’s This All About? ` Statistical Debugging & Cooperative Bug Isolation ` Observe deployed software in the hands of real end users ` Build statistical models of success & failure ` Guide programmers to the root causes of bugs ` Make software suck less ` Lecture plan 1. Motivation for post-deployment debugging 2. Instrumentation and feedback 3. Statistical modeling and (some) program analysis 4. Crazy hacks, cool tricks, & practical considerations Credit Where Credit is Due ` Alex Aiken ` Akash Lal ` David Andrzejewski ` Junghee Lim ` Piramanayagam ` Mayur Naik Arumuga Nainar ` Jake Rosin ` Ting Chen ` Umair Saeed ` Greg Cooksey ` Alice Zheng ` Evan Driscoll ` Xiaojin Zhu ` Jason Fletchall ` … and an anonymous ` Michael Jordan cast of thousands! ` Anne Mulhern ` Or maybe just hundreds? ` Garrett Kolpin ` I don’t really know Motivations: Software Quality in the Real World “There are no significant bugs in our released software that any significant number of users want fixed.” Bill Gates, quoted in FOCUS Magazine A Caricature of Software Development Requirements Architecture & Design Implementation Testing & Verification Maintenance A Caricature of Software Development Requirements Architecture & Design Implementation Testing & Verification Maintenance Software Releases in the Real World [Disclaimer: this may also be a caricature.] Software Releases in the Real World 1. Coders & testers in tight feedback loop ` Detailed monitoring, high repeatability ` Testing approximates
    [Show full text]
  • A Crash Reporting Library for Android
    Masaryk University Faculty of Informatics A Crash Reporting Library for Android Master’s Thesis Marek Osvald Brno, Autumn 2017 Masaryk University Faculty of Informatics A Crash Reporting Library for Android Master’s Thesis Marek Osvald Brno, Autumn 2017 This is where a copy of the official signed thesis assignment and a copy ofthe Statement of an Author is located in the printed version of the document. Declaration Hereby I declare that this paper is my original authorial work, which I have worked out on my own. All sources, references, and literature used or excerpted during elaboration of this work are properly cited and listed in complete reference to the due source. Marek Osvald Advisor: prof. RNDr. Václav Matyáš M.Sc. Ph.D. i Acknowledgement This work was carried out during the years 2016-2017 at AVG Technolo- gies CZ and the Faculty of Informatics at the Masaryk University in Brno. It is a pleasure to use this page to sincerely thank all the people contributing or otherwise involved in the development of this thesis. I owe my deepest gratitude to my thesis supervisor, professor Václav Matyáš. His continuous support helped me to write a thesis worthy of a prestigious institution such as the Masaryk University. I am deeply grateful to my technical supervisor Petr Koudelka for his continuous optimism and guidance during the development. His advise helped me on countless occasions. I would like to express my most sincere gratitude to Philip M. Gammon who answered my English-related questions and selflessly offered proofreading this text. I am particularly grateful for support given by Katarína Varačková and Petr Buno during the initial prototype development.
    [Show full text]
  • Stephen a Ridley
    Escaping The Sandbox (Summer 2010) SyScan-EuSecWest-ReCon Stephen A. Ridley Senior Researcher Matasano Security [email protected] @s7ephen (Twitter) Thursday, July 15, 2010 Who I am. Stephen A. Ridley Senior Security Researcher (Matasano) • Previously: Senior Security Architect at McAfee, founding member of Security Architecture Group • Prior to that: Researcher at leading Defense contractor. Directly supported U.S. Defense and Intelligence communities in realm of software exploitation and software reverse engineering • Columnist for/interviewed by IT magazines (Wired, Ping!, Washington Post) • Kenshoto DefCon CTF organizers for a few years • blog: http://www.dontstuffbeansupyournose.com • Guest Lecturer/Instructor (New York University, Netherlands Forensics Institute, Department of Defense, Google, et al) • My Focus: software reverse engineering, software development, software exploitation, software security, Kernels (Microsoft ones for now). Increasingly interested in embedded systems and mobile devices Thursday, July 15, 2010 What am I talkin’ ‘bout today? ★ Sandboxing Overview (very brief ;-) • Goals, Sandbox Architecture (Chrome) ★ Sandboxes from a User-space Perspective • Securable Objects and SID apertures • Patches/Hooks/Interception • user32 issues ★ Sandboxes from a Kernel-space Perspective • Between User-space and Kernel-space • Kernel supported “Quasi Securable Objects”, Native API • Job Objects handle the rest, or do they? ★ Tools/Techniques/Demos • SandKit Toolkit (code injection, copymem, memdiff, hookfix, sa7shell, bincompare, dumptoken, tokenbrute, handlebrute) • Using Sandbox PoC Project (from Google) • Using kernel debugger while attacking Chrome • Triggering Chrome Bugs and where to start Thursday, July 15, 2010 Presentation Focus ★ Sandbox implementations are (by their nature) strongly coupled to the Operating System ★ This presentation focuses on Microsoft Windows Operating Systems and the NT Kernel (XP and Vista) • Side Note: Check out OSX’s DAC/Sandbox.
    [Show full text]
  • Look 360: an Android Application Using Google Analytics and Firebase with Mobile Cloud Computing
    International Journal of Scientific & Engineering Research Volume 12, Issue 3, March-2021 ISSN 2229-5518 50 Look 360: An android application using Google analytics and firebase with Mobile Cloud Computing. Rawat Deepak Umesh Prathamesh Sonawane Swapnil H Patil UG Student,PHCASC,Rasayani UG Student,PHCASC,Rasayani Asst.Professor ,PHCASC,Rasayani [email protected] [email protected] [email protected] 8355974361 8308380232 9699900007 Abstract— Look 360 is an Android Mobile Application; the name “Look360” originates by keeping its features in mind and considering its capabilities of storing Events, Seminars, Trade Shows and Conferences all across India on the Basis of different categories which has high search index as well as interest of the Students and Educators. Since, Look 360 handles the storing Events, Seminars, Trade Shows and Conferences Nationwide; filtration plays an important role here. This Android Application is connected with Google Firebase which uses Real Time Database feature. Using Real-Time Database enables the system to make changes with respect to Names of events, Date and Time and Venue of events too as specified by the Organizing Team. In order to make a Fully Dynamic Native Android Application the static contents need to be connected with the Cloud, thus Firebase Remote Config comes in picture to make Text, Colour etc feel dynamic. Look 360 is integrated with Google Action which can be evoked by just saying, “Ok Google, Talk to Look 360” where users can Operates the Application based on Voice Command. Google Action used Artificial Intelligence to get output based on Human Interactions via Keyboard or Voice. This Dynamic Android Application not only have Interesting User Interface (UI) but also it built by keeping User Experience (UX) among top priorities.
    [Show full text]
  • Ingimp: Introducing Instrumentation to an End-User Open Source Application Michael Terry, Matthew Kay, Brad Van Vugt, Brandon Slack, Terry Park David R
    ingimp: Introducing Instrumentation to an End-User Open Source Application Michael Terry, Matthew Kay, Brad Van Vugt, Brandon Slack, Terry Park David R. Cheriton School of Computer Science University of Waterloo Waterloo, ON, Canada [email protected], {matthew.kay, bvanvugt, brandon.slack, t2park.uw}@gmail.com ABSTRACT Source code repositories, bug tracking systems, and even Open source projects are gradually incorporating usability tools as simple as “patch” all help to coordinate the methods into their development practices, but there are still activities of individuals who may never meet face-to-face. many unmet needs. One particular need for nearly any open Importantly, these tools not only coordinate project source project is data that describes its user base, including members, they also open up the development process to the information indicating how the software is actually used in larger community: Individuals external to an open source practice. This paper presents the concept of open project can download the source code, fix bugs they instrumentation, or the augmentation of an open source discover, submit patches, or simply report a bug, all without application to openly collect and publicly disseminate rich needing any special credentials or access rights to do so. application usage data. We demonstrate the concept of open The ability for anyone to participate is often cited as a instrumentation in ingimp, a version of the open source potent catalyst for the creation of open source software GNU Image Manipulation Program that has been modified [19]. to collect end-user usage data. ingimp automatically collects five types of data: The commands used, high-level While a mature set of tools scaffold open source software user interface events, overall features of the user’s development, comparatively fewer tools exist to scaffold documents, summaries of the user’s general computing usability efforts in open source projects [1, 14].
    [Show full text]